Please use this identifier to cite or link to this item:
http://hdl.handle.net/1893/35734
Appears in Collections: | Biological and Environmental Sciences Journal Articles |
Peer Review Status: | Refereed |
Title: | resevol: An R package for spatially explicit models of pesticide resistance given evolving pest genomes |
Author(s): | Duthie, A. Bradley Mangan, Rosie McKeon, C Rose Tinsley, Matthew C Bussière, Luc F. |
Contact Email: | alexander.duthie@stir.ac.uk |
Keywords: | Computational Theory and Mathematics Cellular and Molecular Neuroscience Genetics Molecular Biology Ecology Modeling and Simulation Ecology, Evolution, Behavior and Systematics |
Issue Date: | 4-Dec-2023 |
Date Deposited: | 15-Feb-2024 |
Citation: | Duthie AB, Mangan R, McKeon CR, Tinsley MC & Bussière LF (2023) resevol: An R package for spatially explicit models of pesticide resistance given evolving pest genomes. Noble R (Editor) <i>PLOS Computational Biology</i>, 19 (12), Art. No.: e1011691. https://doi.org/10.1371/journal.pcbi.1011691 |
Abstract: | The evolution of pesticide resistance is a widespread problem with potentially severe consequences for global food security. We introduce the resevol R package, which simulates individual-based models of pests with evolving genomes that produce complex, polygenic, and covarying traits affecting pest life history and pesticide resistance. Simulations are modelled on a spatially-explicit and highly customisable landscape in which crop and pesticide application and rotation can vary, making the package a highly flexible tool for both general and tactical models of pest management and resistance evolution. We present the key features of the resevol package and demonstrate its use for a simple example simulating pests with two covarying traits. The resevol R package is open source under GNU Public License. All source code and documentation are available on GitHub. |
DOI Link: | 10.1371/journal.pcbi.1011691 |
Rights: | Copyright: © 2023 Duthie et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Licence URL(s): | http://creativecommons.org/licenses/by/4.0/ |
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journal.pcbi.1011691.pdf | Fulltext - Published Version | 636.25 kB | Adobe PDF | View/Open |
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